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Found 8 papers, 3 papers with code
Multi-Layer Dense Attention Decoder for Polyp Segmentation
Detecting and segmenting polyps is crucial for expediting the diagnosis of colon cancer.
Model-free Resilient Controller Design based on Incentive Feedback Stackelberg Game and Q-learning
In the swift evolution of Cyber-Physical Systems (CPSs) within intelligent environments, especially in the industrial domain shaped by Industry 4. 0, the surge in development brings forth unprecedented security challenges.
On the Detectability of ChatGPT Content: Benchmarking, Methodology, and Evaluation through the Lens of Academic Writing
In this paper, we aim to present a comprehensive study of the detectability of ChatGPT-generated content within the academic literature, particularly focusing on the abstracts of scientific papers, to offer holistic support for the future development of LLM applications and policies in academia.
Learning Generalizable Latent Representations for Novel Degradations in Super Resolution
The real-world degradations can be beyond the simulation scope by the handcrafted degradations, which are referred to as novel degradations.
Hide and Seek: on the Stealthiness of Attacks against Deep Learning Systems
In this paper, we present the first large-scale study on the stealthiness of adversarial samples used in the attacks against deep learning.
Aggregating Global Features into Local Vision Transformer
Local Transformer-based classification models have recently achieved promising results with relatively low computational costs.
Generative Memory-Guided Semantic Reasoning Model for Image Inpainting
Most existing methods for image inpainting focus on learning the intra-image priors from the known regions of the current input image to infer the content of the corrupted regions in the same image.
Two Souls in an Adversarial Image: Towards Universal Adversarial Example Detection using Multi-view Inconsistency
To this end, Argos first amplifies the discrepancies between the visual content of an image and its misclassified label induced by the attack using a set of regeneration mechanisms and then identifies an image as adversarial if the reproduced views deviate to a preset degree.
